EmbeddinghubFeatureform
|
Universal Sentence EncoderTensorflow
|
|||||
Related Products
|
||||||
About
Operationalize your embeddings with one simple tool. Experience a comprehensive database designed to provide embedding functionality that, until now, required multiple platforms. Elevate your machine learning quickly and painlessly through Embeddinghub.
Embeddings are dense, numerical representations of real-world objects and relationships, expressed as vectors. They are often created by first defining a supervised machine learning problem, known as a "surrogate problem." Embeddings intend to capture the semantics of the inputs they were derived from, subsequently getting shared and reused for improved learning across machine learning models. Embeddinghub lets you achieve this in a streamlined, intuitive way.
|
About
The Universal Sentence Encoder (USE) encodes text into high-dimensional vectors that can be utilized for tasks such as text classification, semantic similarity, and clustering. It offers two model variants: one based on the Transformer architecture and another on Deep Averaging Network (DAN), allowing a balance between accuracy and computational efficiency. The Transformer-based model captures context-sensitive embeddings by processing the entire input sequence simultaneously, while the DAN-based model computes embeddings by averaging word embeddings, followed by a feedforward neural network. These embeddings facilitate efficient semantic similarity calculations and enhance performance on downstream tasks with minimal supervised training data. The USE is accessible via TensorFlow Hub, enabling seamless integration into various applications.
|
|||||
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
|||||
Audience
Machine learning developers interested in a powerful vector/embeddings database
|
Audience
Data scientists and machine learning engineers seeking a tool to optimize their natural language processing models with robust sentence embeddings
|
|||||
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
|||||
API
Offers API
|
API
Offers API
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
Free
Free Version
Free Trial
|
Pricing
No information available.
Free Version
Free Trial
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
|||||
Company InformationFeatureform
Founded: 2019
United States
www.featureform.com/embeddinghub
|
Company InformationTensorflow
Founded: 2015
United States
www.tensorflow.org/hub/tutorials/semantic_similarity_with_tf_hub_universal_encoder
|
|||||
Alternatives |
Alternatives |
|||||
|
|
||||||
|
|
||||||
|
|
|
|||||
|
|
|
|||||
Categories |
Categories |
|||||
Integrations
Google Colab
TensorFlow
|
||||||
|
|
|